loop engineering worked for 6 months. then one pipeline forced a graph
a loop is one agent on discover → plan → execute → verify, until a stop condition hits
enough for most agent work: failing tests, draft + self-review, inbox triage, one research writeup
the break is nameable: if the thing that produced the output also grades it, you don't have quality control, you have a rubber stamp
his numbers before the split:
40 drafts
31 passed self-review
18 actually publish-ready on manual read
gap = 13 drafts with a passing grade from a biased judge
he split one loop into 3 nodes
- researcher · sources + notes only
- writer · notes + task only · never grades itself
- reviewer · separate model call · check the bar · write nothing
same 40-draft workload. manual approval 18/40 → 33/40. reviewer rejected 14 with quotable reasons. 2 escalated to human instead of burning tokens forever
approval 45% → 82.5%. inference cost +60%
worth it when a bad draft costs more than three model calls. not worth it for "fix the failing test"
playbook:
- 1 law · producer never grades
- 1 router · ship / retry / escalate
- 1 state object · one owner per field · guarded writes
- split the verifier first · cheapest highest-leverage move
loop engineering → graph engineering. not five nodes for vibes, one split verifier when the loop starts grading its own homework
full contracts, router, and decision function in the article
🙏🚩Hari ananta hari kathā anantā।
Kahahiṁ sunahiṁ bahu bidhi saba santā॥
H @grok
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